Association mapping of loci controlling genetic and environmental interaction of soybean flowering time under various photo-thermal conditions

The Effects of Different Durations of Night-Time Supplementary Lighting on the Growth, Yield, Quality and Economic Returns of Tomato

To achieve higher economic returns, we employ inexpensive valley electricity for night-time supplementary lighting (NSL) of tomato plants, investigating the effects of various durations of NSL on the growth, yield, and quality of tomato. Tomato plants were treated with supplementary light for a period of 0 h, 3 h, 4 h, and 5 h during the autumn-winter season. The findings revealed superior growth and yield of tomato plants exposed to 3 h, 4 h, and 5 h of NSL compared to their untreated counterparts. Notably, providing lighting for 3 h demonstrated greater yields per plant and per trough than 5 h exposure. To investigate if a reduced duration of NSL would display similar effects on the growth and yield of tomato plants, tomato plants received supplementary light for 0 h, 1 h, 2 h, and 3 h at night during the early spring season. Compared to the control group, the stem diameter, chlorophyll content, photosynthesis rate, and yield of tomatoes significantly increased upon supplementation with lighting. Furthermore, the input-output ratios of 1 h, 2 h, and 3 h NSL were calculated as 1:10.11, 1:4.38, and 1:3.92, respectively. Nonetheless, there was no detectable difference in yield between the 1 h, 2 h, and 3 h NSL groups. These findings imply that supplemental LED lighting at night affects tomato growth in the form of light signals. Night-time supplemental lighting duration of 1 h is beneficial to plant growth and yield, and its input-output ratio is the lowest, which is an appropriate NSL mode for tomato cultivation.

Flowering time regulator qFT13-3 involved in soybean adaptation to high latitudes

Soybean is a short-day plant that typically flowers earlier when exposed to short-day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome-wide association studies (GWAS) using two re-sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13-3, which encodes a protein homologous to the pseudo-response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13-3 in the natural population, with haplotype H4 (qFT13-3H4) being lost during domestication, while qFT13-3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13-3H1 were located in high-latitude regions. Knockout of qFT13-3 accelerated flowering and maturity time under long-day conditions, indicating that qFT13-3 functions as a flowering inhibitor. Our results also showed that qFT13-3 directly downregulates the expression of GmELF3b-2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13-3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13-3 can be utilized for the breeding of high-yield cultivars with a short maturity time suitable for high latitudes.

Dissection of the E8 locus in two early maturing Canadian soybean populations

Soybean [Glycine max (L.) Merr.] is a short-day crop for which breeders want to expand the cultivation range to more northern agro-environments by introgressing alleles involved in early reproductive traits. To do so, we investigated quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) regions comprised within the E8 locus, a large undeciphered region (~7.0 Mbp to 44.5 Mbp) associated with early maturity located on chromosome GM04. We used a combination of two mapping algorithms, (i) inclusive composite interval mapping (ICIM) and (ii) genome-wide composite interval mapping (GCIM), to identify major and minor regions in two soybean populations (QS15524F2:F3 and QS15544RIL) having fixed E1, E2, E3, and E4 alleles. Using this approach, we identified three main QTL regions with high logarithm of the odds (LODs), phenotypic variation explained (PVE), and additive effects for maturity and pod-filling within the E8 region: GM04:16,974,874-17,152,230 (E8-r1); GM04:35,168,111-37,664,017 (E8-r2); and GM04:41,808,599-42,376,237 (E8-r3). Using a five-step variant analysis pipeline, we identified Protein far-red elongated hypocotyl 3 (Glyma.04G124300; E8-r1), E1-like-a (Glyma.04G156400; E8-r2), Light-harvesting chlorophyll-protein complex I subunit A4 (Glyma.04G167900; E8-r3), and Cycling dof factor 3 (Glyma.04G168300; E8-r3) as the most promising candidate genes for these regions. A combinatorial eQTL mapping approach identified significant regulatory interactions for 13 expression traits (e-traits), including Glyma.04G050200 (Early flowering 3/E6 locus), with the E8-r3 region. Four other important QTL regions close to or encompassing major flowering genes were also detected on chromosomes GM07, GM08, and GM16. In GM07:5,256,305-5,404,971, a missense polymorphism was detected in the candidate gene Glyma.07G058200 (Protein suppressor of PHYA-105). These findings demonstrate that the locus known as E8 is regulated by at least three distinct genomic regions, all of which comprise major flowering genes.

Genome-wide association study for temperature response and photo-thermal interaction of flowering time in soybean using a panel of cultivars with diverse maturity groups

KEY MESSAGE

A total of 101 QTNs were found to be associated with soybean flowering time responses to photo-thermal conditions; three candidate genes with non-synonymous substitutions were identified: Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). The flowering transition is a crucial component of soybean (Glycine max L. Merr.) development. The transition process is regulated by photoperiod, temperature, and their interaction. To examine the genetic architecture associated with temperature- and photo-thermal-mediated regulation of soybean flowering, we here performed a genome-wide association study using a panel of 201 soybean cultivars with maturity groups ranging from MG 000 to VIII. Each cultivar was grown in artificially controlled photoperiod and different seasons in 2017 and 2018 to assess the thermal response (TR) and the interactive photo-thermal response (IPT) of soybean flowering time. The panel contained 96,299 SNPs with minor allele frequencies > 5%; 33, 19, and 49 of these SNPs were significantly associated with only TR, only IPT, and both TR and IPT, respectively. Twenty-one SNPs were located in or near previously reported quantitative trait loci for first-flowering; 16 SNPs were located within 200 kb of the main-effect flowering genes GmFT2a, GmFT2b, GmFT3a, GmFT3b, GmFT5a, GmFT5b, GmCOL2b, GmPIF4b, and GmPIF4c, or near homologs of the known Arabidopsis thaliana flowering genes BBX19, VRN1, TFL1, FUL, AGL19, SPA1, HY5, PFT1, and EDF1. Natural non-synonymous allelic variations were identified in the candidate genes Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). Cultivars with different haplotypes showed significant variations in TR, IPT, and flowering time in multiple environments. The favorable alleles, candidate genes, and diagnostic SNP markers identified here provide valuable information for future improvement of soybean photo-thermal adaptability, enabling expansion of soybean production regions and improving plant resilience to global climate change.

Molecular breeding for improvement of photothermal adaptability in soybean

Soybean (Glycine max (L.) Merr.) is a typical short-day and temperate crop that is sensitive to photoperiod and temperature. Responses of soybean to photothermal conditions determine plant growth and development, which affect its architecture, yield formation, and capacity for geographic adaptation. Flowering time, maturity, and other traits associated with photothermal adaptability are controlled by multiple major-effect and minor-effect genes and genotype-by-environment interactions. Genetic studies have identified at least 11 loci (E1-E4, E6-E11, and J) that participate in photoperiodic regulation of flowering time and maturity in soybean. Molecular cloning and characterization of major-effect flowering genes have clarified the photoperiod-dependent flowering pathway, in which the photoreceptor gene phytochrome A, circadian evening complex (EC) components, central flowering repressor E1, and FLOWERING LOCUS T family genes play key roles in regulation of flowering time, maturity, and adaptability to photothermal conditions. Here, we provide an overview of recent progress in genetic and molecular analysis of traits associated with photothermal adaptability, summarizing advances in molecular breeding practices and tools for improving these traits. Furthermore, we discuss methods for breeding soybean varieties with better adaptability to specific ecological regions, with emphasis on a novel strategy, the Potalaization model, which allows breeding of widely adapted soybean varieties through the use of multiple molecular tools in existing elite widely adapted varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01406-z.

The genetic architecture of soybean photothermal adaptation to high latitudes

Soybean is a major plant protein source for both human food and animal feed, but to meet global demands as well as a trend towards regional production, soybean cultivation needs to be expanded to higher latitudes. In this study, we developed a large diversity panel consisting of 1503 early-maturing soybean lines and used genome-wide association mapping to dissect the genetic architecture underlying two crucial adaptation traits, flowering time and maturity. This revealed several known maturity loci, E1, E2, E3, and E4, and the growth habit locus Dt2 as causal candidate loci, and also a novel putative causal locus, GmFRL1, encoding a homolog of the vernalization pathway gene FRIGIDA-like 1. In addition, the scan for quantitative trait locus (QTL)-by-environment interactions identified GmAPETALA1d as a candidate gene for a QTL with environment-dependent reversed allelic effects. The polymorphisms of these candidate genes were identified using whole-genome resequencing data of 338 soybeans, which also revealed a novel E4 variant, e4-par, carried by 11 lines, with nine of them originating from Central Europe. Collectively, our results illustrate how combinations of QTL and their interactions with the environment facilitate the photothermal adaptation of soybean to regions far beyond its center of origin.

Diverse flowering responses subjecting to ambient high temperature in soybean under short-day conditions

Flowering time is one of important agronomic traits determining the crop yield and affected by high temperature. When facing high ambient temperature, plants often initiate early flowering as an adaptive strategy to escape the stress and ensure successful reproduction. However, here we find opposing ways in the short-day crop soybean to respond to different levels of high temperatures, in which flowering accelerates when temperature changes from 25 to 30 °C, but delays when temperature reaches 35 °C under short day. phyA-E1, possibly photoperiodic pathway, is crucial for 35 °C-mediated late flowering, however, does not contribute to promoting flowering at 30 °C. 30 °C-induced up-regulation of FT2a and FT5a leads to early flowering, independent of E1. Therefore, distinct responsive mechanisms are adopted by soybean when facing different levels of high temperatures for successful flowering and reproduction.

High-quality genome assembly and pan-genome studies facilitate genetic discovery in mung bean and its improvement

Mung bean is an economically important legume crop species that is used as a food, consumed as a vegetable, and used as an ingredient and even as a medicine. To explore the genomic diversity of mung bean, we assembled a high-quality reference genome (Vrad_JL7) that was ∼479.35 Mb in size, with a contig N50 length of 10.34 Mb. A total of 40,125 protein-coding genes were annotated, representing ∼96.9% of the genetic region. We also sequenced 217 accessions, mainly landraces and cultivars from China, and identified 2,229,343 high-quality single-nucleotide polymorphisms (SNPs). Population structure revealed that the Chinese accessions diverged into two groups and were distinct from non-Chinese lines. Genetic diversity analysis based on genomic data from 750 accessions in 23 countries supported the hypothesis that mung bean was first domesticated in south Asia and introduced to east Asia probably through the Silk Road. We constructed the first pan-genome of mung bean germplasm and assembled 287.73 Mb of non-reference sequences. Among the genes, 83.1% were core genes and 16.9% were variable. Presence/absence variation (PAV) events of nine genes involved in the regulation of the photoperiodic flowering pathway were identified as being under selection during the adaptation process to promote early flowering in the spring. Genome-wide association studies (GWASs) revealed 2,912 SNPs and 259 gene PAV events associated with 33 agronomic traits, including a SNP in the coding region of the SWEET10 homolog (jg24043) involved in crude starch content and a PAV event in a large fragment containing 11 genes for color-related traits. This high-quality reference genome and pan-genome will provide insights into mung bean breeding.

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool

In this study, we performed a genotyping-by-sequencing analysis and a genome-wide association study of a soybean mutant diversity pool previously constructed by gamma irradiation. A GWAS was conducted to detect significant associations between 37,249 SNPs, 11 agronomic traits, and 6 phytochemical traits. In the merged data set, 66 SNPs on 13 chromosomes were highly associated (FDR p < 0.05) with the following 4 agronomic traits: days of flowering (33 SNPs), flower color (16 SNPs), node number (6 SNPs), and seed coat color (11 SNPs). These results are consistent with the findings of earlier studies on other genetic features (e.g., natural accessions and recombinant inbred lines). Therefore, our observations suggest that the genomic changes in the mutants generated by gamma irradiation occurred at the same loci as the mutations in the natural soybean population. These findings are indicative of the existence of mutation hotspots, or the acceleration of genome evolution in response to high doses of radiation. Moreover, this study demonstrated that the integration of GBS and GWAS to investigate a mutant population derived from gamma irradiation is suitable for dissecting the molecular basis of complex traits in soybeans.

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.

Genetic Diversity and Selection Footprints in the Genome of Brazilian Soybean Cultivars

Although Brazil is currently the largest soybean producer in the world, only a small number of studies have analyzed the genetic diversity of Brazilian soybean. These studies have shown the existence of a narrow genetic base. The objectives of this work were to analyze the population structure and genetic diversity, and to identify selection signatures in the genome of soybean germplasms from different companies in Brazil. A panel consisting of 343 soybean lines from Brazil, North America, and Asia was genotyped using genotyping by sequencing (GBS). Population structure was assessed by Bayesian and multivariate approaches. Genetic diversity was analyzed using metrics such as the fixation index, nucleotide diversity, genetic dissimilarity, and linkage disequilibrium. The software BayeScan was used to detect selection signatures between Brazilian and Asian accessions as well as among Brazilian germplasms. Region of origin, company of origin, and relative maturity group (RMG) all had a significant influence on population structure. Varieties belonging to the same company and especially to the same RMG exhibited a high level of genetic similarity. This result was exacerbated among early maturing accessions. Brazilian soybean showed significantly lower genetic diversity when compared to Asian accessions. This was expected, because the crop's region of origin is its main genetic diversity reserve. We identified 7 genomic regions under selection between the Brazilian and Asian accessions, and 27 among Brazilian varieties developed by different companies. Associated with these genomic regions, we found 96 quantitative trait loci (QTLs) for important soybean breeding traits such as flowering, maturity, plant architecture, productivity components, pathogen resistance, and seed composition. Some of the QTLs associated with the markers under selection have genes of great importance to soybean's regional adaptation. The results reported herein allowed to expand the knowledge about the organization of the genetic variability of the Brazilian soybean germplasm. Furthermore, it was possible to identify genomic regions under selection possibly associated with the adaptation of soybean to Brazilian environments.

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Speed-Breeding System in Soybean: Integrating Off-Site Generation Advancement, Fresh Seeding, and Marker-Assisted Selection

Speed breeding by artificial control of photothermal conditions facilitates generation advancement but was limited in scale and cost. In this study, we demonstrated a cost-saving off-site summer nursery pattern, taking full advantage of shorter daylength and higher temperature with lower latitude compared to the origin of the soybean cultivars used in the study. This substantially reduced the generation cycles under totally natural conditions. Using this approach, two generations of soybean cultivars from Northeastern Spring Planting Region (NE) and Yellow-Huai-Hai Valleys Summer Planting Region (YHH) were successfully obtained in Beijing and Hainan, respectively, compared to one generation in origin. Fresh-seeding method was also used to further shorten the generation duration by 7-10 days, thereby allowing at least four generations per year. Using DNA markers to define haplotypes of maturity genes E1-E4, we proposed a model to predict the optimum adaptation region of the advanced generation lines. Taken together, we present a speed-breeding methodology combining off-site nursery, fresh-seeding method, and marker-assisted selection, aimed at accelerating soybean improvement.

Genome-wide association analysis for yield-related traits at the R6 stage in a Chinese soybean mini core collection

BACKGROUND

Soybean (Glycine max (L.) Merr.) is an economically important crop for vegetable oil and protein production, and yield is a critical trait for grain/vegetable uses of soybean. However, our knowledge of the genes controlling the vegetable soybean yield remains limited.

OBJECTIVE

To better understand the genetic basis of the vegetable soybean yield.

METHODS

The 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), kernel percent (KP) and moisture content of fresh seeds (MCFS) at the R6 stage are four yield-related traits for vegetable soybean. We investigated a soybean mini core collection composed of 224 germplasm accessions for four yield-related traits in two consecutive years. Based on 1514 single nucleotide polymorphisms (SNPs), genome-wide association studies (GWAS) were conducted using a mixed linear model (MLM).

RESULTS

Extensive phenotypic variation existed in the soybean mini core collection and significant positive correlations were shown among most of traits. A total of 16 SNP markers for PFW, SFW, KP and MCFS were detected in all environments via GWAS. Nine SNP markers were repeatedly identified in two environments. Among these markers, eight were located in or near regions where yield-related QTLs have been reported in previous studies, and one was a novel genetic locus identified in this study. In addition, we conducted candidate gene analysis to the large-effect SNP markers, a total of twelve genes were proposed as potential candidate genes of soybean yield at the R6 stage.

CONCLUSION

These results will be beneficial for understanding the genetic basis of soybean yield at the R6 stage and facilitating the pyramiding of favourable alleles for future high-yield breeding by marker-assisted selection in vegetable soybean.

Genome-Wide Association Study Reveals Candidate Genes for Flowering Time in Cowpea (Vigna unguiculata [L.] Walp.)

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 368 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

Identification of QTNs and their candidate genes for flowering time and plant height in soybean using multi-locus genome-wide association studies

Flowering time (FT) and plant height (PH) are important agronomic traits in soybean. However, their genetic foundations are not fully understood. Thus, in this study, a total of 106,013 single nucleotide polymorphisms in 286 soybean accessions were used to associate with the first and full FT (FT1 and FT2) and PH in 4 environments and their BLUP values using 6 multi-locus genome-wide association study methods. As a result, 38, 43, and 27 stable quantitative trait nucleotides (QTNs) were identified, respectively, for FT1, FT2, and PH across at least 3 methods and/or environments. Among these QTNs for FT1, FT2, and PH, 31, 36, and 21 were found to have significant phenotype differences across 2 alleles; 22, 18, and 13 were consistent with the corresponding loci in previous studies; 13 and 8 genes, with more than average expression level, around 64 FT and 27 PH QTNs were predicted as their corresponding candidate genes. Among these candidate genes, GmPRR3b, and GmGIa for FT, and GmTFL1b for PH were known, while some were new, e.g., GmPHYA4, GmVRN5, GmFPA, and GmSPA1 for FT, and Glyma.02g300200, GmFPA, and Glyma.13g339800 for PH. All the validated QTNs were used to design the best cross-combinations in 2 FT directions. In each FT direction, the best 5 cross-combinations were predicted, such as Heihe 54 × Qincha 1 for early FT, and Yingdejiadou × Wuhuabayuehuang for late FT. This study provides solid foundations for genetic basis, molecular biology, and breeding by design of soybean FT and PH.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01230-3.

A flowering time locus dependent on E2 in soybean

Soybean [Glycine max (L.) Merrill] is very sensitive to changes in photoperiod as a typical short-day plant. Photoperiodic flowering influences soybean latitudinal adaptability and yield to a considerable degree. Identifying new quantitative trait loci (QTLs) controlling flowering time is a powerful initial approach for elucidating the mechanisms underlying flowering time and adaptation to different latitudes in soybean. In this study, we developed a Recombinant Inbred Lines (RILs) population and recorded flowering time under natural long-day conditions. We also constructed a high-density genetic map by genotyping-by-sequencing and used it for QTL mapping. In total, we detected twelve QTLs, four of which are stable and named by qR1-2, qR1-4, qR1-6.1, and qR1-10, respectively. Among these four QTLs, qR1-4 and qR1-6.1 are novel. QTL mapping in two sub-populations classified by the genotype of the maturity locus E2, genetic interaction evaluation between E2 and qR1-2, and qRT-PCR indicated that E2 has an epistatic effect on qR1-2, and that causal gene of qR1-2 acts upstream of E2. We presumed the most likely candidate genes according to the resequencing data and briefly analyzed the geographic distributions of these genes. These findings will be beneficial for our understanding of the mechanisms underlying photoperiodic flowering in soybean, contribute to further investigate of E2, and provide genetic resources for molecular breeding of soybean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01224-1.

A Domestication-Associated Gene GmPRR3b Regulates the Circadian Clock and Flowering Time in Soybean

Improved soybean cultivars have been adapted to grow at a wide range of latitudes, enabling expansion of cultivation worldwide. However, the genetic basis of this broad adaptation is still not clear. Here, we report the identification of GmPRR3b as a major flowering time regulatory gene that has been selected during domestication and genetic improvement for geographic expansion. Through a genome-wide association study of a diverse soybean landrace panel consisting of 279 accessions, we identified 16 candidate quantitative loci associated with flowering time and maturity time. The strongest signal resides in the known flowering gene E2, verifying the effectiveness of our approach. We detected strong signals associated with both flowering and maturity time in a genomic region containing GmPRR3b. Haplotype analysis revealed that GmPRR3bH6 is the major form of GmPRR3b that has been utilized during recent breeding of modern cultivars. mRNA profiling analysis showed that GmPRR3bH6 displays rhythmic and photoperiod-dependent expression and is preferentially induced under long-day conditions. Overexpression of GmPRR3bH6 increased main stem node number and yield, while knockout of GmPRR3bH6 using CRISPR/Cas9 technology delayed growth and the floral transition. GmPRR3bH6 appears to act as a transcriptional repressor of multiple predicted circadian clock genes, including GmCCA1a, which directly upregulates J/GmELF3a to modulate flowering time. The causal SNP (Chr12:5520945) likely endows GmPRR3bH6 a moderate but appropriate level of activity, leading to early flowering and vigorous growth traits preferentially selected during broad adaptation of landraces and improvement of cultivars.

Exploring the genetic base of the soybean germplasm from Africa, America and Asia as well as mining of beneficial allele for flowering and seed weight

Genetic diversity is the foundation for any breeding program. The present study analyzed the genetic base of 163 soybean genotypes from three continents viz. Africa, America and Asia using 68 trait-linked simple sequence repeats (SSR) markers. The average number of alleles among the germplasm from the three continents followed the trend as Asia (9) > America (8) > Africa (7). Similar trends were observed for gene diversity (0.76 > 0.74 > 0.71) and polymorphism information content (PIC) (0.73 > 0.71 > 0.68). These findings revealed that soybean germplasm from Asia has wider genetic base followed by America, and least in Africa. The 163 genotypes were grouped into 4 clusters by phylogenetic analysis, whereas model-based population structure analysis also divided them into 4 subpopulations comprising 80.61% pure lines and 19.39% admixtures. The genotypes from Africa were easily distinguished from those of other two continents using phylogenetic analysis, indicating important role of geographyical differentiation for this genetic variability. Our results indicated that soybean germplasm has moved from Asia to America, and from America to Africa. Analysis of molecular variance (AMOVA) showed 8.41% variation among the four subpopulations, whereas 63.12% and 28.47% variation existed among and within individuals in the four subpopulations, respectively. Based on the association mapping, a total of 21 SSR markers showed significant association with days to flowering (DoF) and 100-seed weight (HSW). Two markers Satt365 and Satt581 on chromosome 6 and 10, respectively, showed pleiotropic effect or linkage on both traits. Genotype A50 (Gakuran Daizu/PI 506679) from Japan has 8 out of the 13 beneficial alleles for increased HSW. The diverse genotypes, polymorphic SSR markers and desirable alleles identified for DoF and HSW will be used in future breeding programs to improve reproductive, yield and quality traits.

GWAS reveals two novel loci for photosynthesis-related traits in soybean

Photosynthesis plays an extremely important role throughout the life cycle of plants. Improving the photosynthetic rate is a major target for increasing crop productivity. This study was conducted to identify single nucleotide polymorphisms (SNPs) associated with the net photosynthetic rate (Pn), stomatal conductance (Cond), intercellular carbon dioxide concentration (Ci) and transpiration rate (Trmmol) through genome-wide association study (GWAS) and to inspect the relationships among these traits in soybean (Glycine max (L.) Merr.). A population of 219 soybean accessions was used in this research. A total of 12 quantitative trait loci (QTLs) associated with Pn, Cond, Ci and Trmmol were detected and distributed on chromosomes 1, 2, 6, 7, 9, 11, 12, 13, 15, 16, 18, and 19, and some of these QTL overlapped with previously reported QTLs. Furthermore, four candidate genes were identified, and there were significantly different expression levels between the high-light-efficiency accessions and low-light-efficiency accessions. These putative genes may participate in the regulation of photosynthesis through different metabolic pathways. Therefore, the associated novel QTLs and candidate genes detected in this study will provide a theoretical basis for genetic studies of photosynthesis and provide new avenues for crop improvement.

A Soybean Deletion Mutant That Moderates the Repression of Flowering by Cool Temperatures

Ambient growing temperature and photoperiod are major environmental stimuli that summer annual crops use to adjust their reproductive phenology so as to maximize yield. Variation in flowering time among soybean (Glycine max) cultivars results mainly from allelic diversity at loci that control photoperiod sensitivity and FLOWERING LOCUS T (FT) orthologs. However, variation in the thermal regulation of flowering and its underlying mechanisms are poorly understood. In this study, we identified a novel mutant (ef1) that confers altered thermal regulation of flowering in response to cool ambient temperatures. Mapping analysis with simple sequence repeat (SSR) markers located the mutation in the upper part of chromosome 19, where no QTL for flowering has been previously reported. Fine-mapping and re-sequencing revealed that the mutation was caused by deletion of a 214 kbp genomic region that contains 11 annotated genes, including CONSTANS-LIKE 2b (COL2b), a soybean ortholog of Arabidopsis CONSTANS. Comparison of flowering times under different photo-thermal conditions revealed that early flowering in the mutant lines was most distinct under cool ambient temperatures. The expression of two FT orthologs, FT2a and FT5a, was dramatically downregulated by cool temperature, but the magnitude of the downregulation was lower in the mutant lines. Cool temperatures upregulated COL2b expression or delayed peak expression, particularly at the fourth trifoliate-leaf stage. Intriguingly, they also upregulated E1, a soybean-specific repressor of FT orthologs. Our results suggest that the ef1 mutation is involved in thermal regulation of flowering in response to cool ambient temperature, and the lack of COL2b in the mutant likely alleviates the repression of flowering by cool temperature. The ef1 mutant can be used as a novel gene resource in breeding soybean cultivars adapted to cool climate and in research to improve our understanding of thermal regulation of flowering in soybean.

Nested association mapping of important agronomic traits in three interspecific soybean populations

KEY MESSAGE

Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.

Identification of loci controlling adaptation in Chinese soya bean landraces via a combination of conventional and bioclimatic GWAS

Landraces often contain genetic diversity that has been lost in modern cultivars, including alleles that confer enhanced local adaptation. To comprehensively identify loci associated with adaptive traits in soya bean landraces, for example flowering time, a population of 1938 diverse landraces and 97 accessions of the wild progenitor of cultivated soya bean, Glycine soja was genotyped using tGBS® . Based on 99 085 high-quality SNPs, landraces were classified into three sub-populations which exhibit geographical genetic differentiation. Clustering was inferred from STRUCTURE, principal component analyses and neighbour-joining tree analyses. Using phenotypic data collected at two locations separated by 10 degrees of latitude, 17 trait-associated SNPs (TASs) for flowering time were identified, including a stable locus Chr12:5914898 and previously undetected candidate QTL/genes for flowering time in the vicinity of the previously cloned flowering genes, E1 and E2. Using passport data associated with the collection sites of the landraces, 27 SNPs associated with adaptation to three bioclimatic variables (temperature, daylength, and precipitation) were identified. A series of candidate flowering genes were detected within linkage disequilibrium (LD) blocks surrounding 12 bioclimatic TASs. Nine of these TASs exhibit significant differences in flowering time between alleles within one or more of the three individual sub-populations. Signals of selection during domestication and/or subsequent landrace diversification and adaptation were detected at 38 of the 44 flowering and bioclimatic TASs. Hence, this study lays the groundwork to begin breeding for novel environments predicted to arise following global climate change.

Identification of genetic loci and candidate genes related to soybean flowering through genome wide association study

BACKGROUND

As a photoperiod-sensitive and self-pollinated species, the growth periods traits play important roles in the adaptability and yield of soybean. To examine the genetic architecture of soybean growth periods, we performed a genome-wide association study (GWAS) using a panel of 278 soybean accessions and 34,710 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) higher than 0.04 detected by the specific-locus amplified fragment sequencing (SLAF-seq) with a 6.14-fold average sequencing depth. GWAS was conducted by a compressed mixed linear model (CMLM) involving in both relative kinship and population structure.

RESULTS

GWAS revealed that 37 significant SNP peaks associated with soybean flowering time or other growth periods related traits including full bloom, beginning pod, full pod, beginning seed, and full seed in two or more environments at -log10(P) > 3.75 or -log10(P) > 4.44 were distributed on 14 chromosomes, including chromosome 1, 2, 3, 5, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19. Fourteen SNPs were novel loci and 23 SNPs were located within known QTLs or 75 kb near the known SNPs. Five candidate genes (Glyma.05G101800, Glyma.11G140100, Glyma.11G142900, Glyma.19G099700, Glyma.19G100900) in a 90 kb genomic region of each side of four significant SNPs (Gm5_27111367, Gm11_10629613, Gm11_10950924, Gm19_34768458) based on the average LD decay were homologs of Arabidopsis flowering time genes of AT5G48385.1, AT3G46510.1, AT5G59780.3, AT1G28050.1, and AT3G26790.1. These genes encoding FRI (FRIGIDA), PUB13 (plant U-box 13), MYB59, CONSTANS, and FUS3 proteins respectively might play important roles in controlling soybean growth periods.

CONCLUSIONS

This study identified putative SNP markers associated with soybean growth period traits, which could be used for the marker-assisted selection of soybean growth period traits. Furthermore, the possible candidate genes involved in the control of soybean flowering time were predicted.

Characterization and quantitative trait locus mapping of late-flowering from a Thai soybean cultivar introduced into a photoperiod-insensitive genetic background

The timing of both flowering and maturation determine crop adaptability and productivity. Soybean (Glycine max) is cultivated across a wide range of latitudes. The molecular-genetic mechanisms for flowering in soybean have been determined for photoperiodic responses to long days (LDs), but remain only partially determined for the delay of flowering under short-day conditions, an adaptive trait of cultivars grown in lower latitudes. Here, we characterized the late-flowering (LF) habit introduced from the Thai cultivar K3 into a photoperiod-insensitive genetic background under different photo-thermal conditions, and we analyzed the genetic basis using quantitative trait locus (QTL) mapping. The LF habit resulted from a basic difference in the floral induction activity and from the suppression of flowering, which was caused by red light-enriched LD lengths and higher temperatures, during which FLOWERING LOCUS T (FT) orthologs, FT2a and FT5a, were strongly down-regulated. QTL mapping using gene-specific markers for flowering genes E2, FT2a and FT5a and 829 single nucleotide polymorphisms obtained from restriction-site associated DNA sequencing detected three QTLs controlling the LF habit. Of these, a QTL harboring FT2a exhibited large and stable effects under all the conditions tested. A resequencing analysis detected a nonsynonymous substitution in exon 4 of FT2a from K3, which converted the glycine conserved in FT-like proteins to the aspartic acid conserved in TERMINAL FLOWER 1-like proteins (floral repressors), suggesting a functional depression in the FT2a protein from K3. The effects of the remaining two QTLs, likely corresponding to E2 and FT5a, were environment dependent. Thus, the LF habit from K3 may be caused by the functional depression of FT2a and the down-regulation of two FT genes by red light-enriched LD conditions and high temperatures.

Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers

As an important and complex trait, inflorescence length (IL) of soybean [Glycine max (L.) Merr.] significantly affected seed yields. Therefore, elucidating molecular basis of inflorescence architecture, especially for IL, was important for improving soybean yield potentials. Longer IL meaned to have more pod and seed in soybean. Hence, increasing IL and improving yield are targets for soybean breeding. In this study, a association panel, comprising 283 diverse samples, was used to dissect the genetic basis of IL based on genome-wide association analysis (GWAS) and haplotype analysis. GWAS and haplotype analysis were conducted through high-throughout single-nucleotide polymorphisms (SNP) developed by SLAF-seq methodology. A total of 39, 057 SNPs (minor allele frequency ≥ 0.2 and missing data ≤ 10%) were utilized to evaluate linkage disequilibrium (LD) level in the tested association panel. A total of 30 association signals were identified to be associated with IL via GWAS. Among them, 13 SNPs were novel, and another 17 SNPs were overlapped or located near the linked regions of known quantitative trait nucleotide (QTN) with soybean seed yield or yield component. The functional genes, located in the 200-kb genomic region of each peak SNP, were considered as candidate genes, such as the cell division/ elongation, specific enzymes, and signaling or transport of specific proteins. These genes have been reported to participant in the regulation of IL. Ten typical long-IL lines and ten typical short-IL lines were re-sequencing, and then, six SNPs from five genes were obtained based on candidate gene-based association. In addition, 42 haplotypes were defined based on haplotype analysis. Of them, 11 haplotypes were found to regulate long IL (> 14 mm) in soybean. The identified 30 QTN with beneficial alleles and their candidate genes might be valuable for dissecting the molecular mechanisms of IL and further improving the yield potential of soybean.

Genome-wide association and transcriptional studies reveal novel genes for unsaturated fatty acid synthesis in a panel of soybean accessions

BACKGROUND

The nutritional value of soybean oil is largely influenced by the proportions of unsaturated fatty acids (FAs), including oleic acid (OA, 18:1), linoleic acid (LLA, 18:2), and linolenic acid (LNA, 18:3). Genome-wide association (GWAS) studies along with gene expression studies in soybean [Glycine max (L.) Merr.] were leveraged to dissect the genetics of unsaturated FAs.

RESULTS

A association panel of 194 diverse soybean accessions were phenotyped in 2013, 2014 and 2015 to identify Single Nucleotide Polymorphisms (SNPs) associated with OA, LLA, and LNA content, and determine putative candidate genes responsible for regulating unsaturated FAs composition. 149 SNPs that represented 73 genomic regions were found to be associated with the unsaturated FA contents in soybean seeds according to the results of GWAS. Twelve novel genes were predicted to be involved in unsaturated FA synthesis in soybean. The relationship between expression pattern of the candidate genes and the accumulation of unsaturated FAs revealed that multiple genes might be involved in unsaturated FAs regulation simultaneously but work in very different ways: Glyma.07G046200 and Glyma.20G245500 promote the OA accumulation in soybean seed in all the tested accessions; Glyma.13G68600 and Glyma.16G200200 promote the OA accumulation only in high OA germplasms; Glyma.07G151300 promotes OA accumulation in higher OA germplasms and suppresses that in lower OA germplasms; Glyma.16G003500 has the effect of increasing LLA accumulation in higher LA germplasms; Glyma.07G254500 suppresses the accumulation of LNA in lower OA germplasms; Glyma.14G194300 might be involved in the accumulation of LNA content in lower LNA germplasms.

CONCLUSIONS

The beneficial alleles and candidate genes identified might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying unsaturated fatty acid of soybean.

Positional Cloning of the Flowering Time QTL qFT12-1 Reveals the Link Between the Clock Related PRR Homolog With Photoperiodic Response in Soybeans

Flowering time and maturity are important agronomic traits for soybean cultivars to adapt to different latitudes and achieve maximal yield. Genetic studies on genes and quantitative trait loci (QTL) that control flowering time and maturity are extensive. In particular, the molecular bases of E1-E4, E6, E9, E10, and J have been deciphered. For a better understanding of regulation of flowering time gene networks, we need to understand if more molecular factors carrying different biological functions are also involved in the regulation of flowering time in soybeans. We developed a population derived from a cross between a landrace Jilincailihua (male) and a Chinese cultivar Chongnong16 (female). Both parents carry the same genotypes of E1e2E3HaE4 at E1, E2, E3, and E4 loci. Nighty-six individuals of the F₂ population were genotyped with Illumina SoySNP8k iSelect BeadChip. A total of 2,407 polymorphic single nucleotide polymorphism (SNP) markers were used to construct a genetic linkage map. One major QTL, qFT12-1, was mapped to an approximately 567-kB region on chromosome 12. Genotyping and phenotyping of recombinant plant whose recombination events were occurring within the QTL region allowed us to narrow down the QTL region to 56.4 kB, in which four genes were annotated. Allelism and association analysis indicated Glyma.12G073900, a PRR7 homolog, is the strongest candidate gene for qFT12-1. The findings of this study disclosed the possible involvement of circadian clock gene in flowering time regulation of soybeans.

Crop genome-wide association study: a harvest of biological relevance

With the advent of rapid genotyping and next-generation sequencing technologies, genome-wide association study (GWAS) has become a routine strategy for decoding genotype-phenotype associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype-phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many 'hits' obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non-main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome-editing technologies.

De novo assembly of a Chinese soybean genome

Soybean was domesticated in China and has become one of the most important oilseed crops. Due to bottlenecks in their introduction and dissemination, soybeans from different geographic areas exhibit extensive genetic diversity. Asia is the largest soybean market; therefore, a high-quality soybean reference genome from this area is critical for soybean research and breeding. Here, we report the de novo assembly and sequence analysis of a Chinese soybean genome for "Zhonghuang 13" by a combination of SMRT, Hi-C and optical mapping data. The assembled genome size is 1.025 Gb with a contig N50 of 3.46 Mb and a scaffold N50 of 51.87 Mb. Comparisons between this genome and the previously reported reference genome (cv. Williams 82) uncovered more than 250,000 structure variations. A total of 52,051 protein coding genes and 36,429 transposable elements were annotated for this genome, and a gene co-expression network including 39,967 genes was also established. This high quality Chinese soybean genome and its sequence analysis will provide valuable information for soybean improvement in the future.

Quantitative Trait Locus Mapping of Flowering Time and Maturity in Soybean Using Next-Generation Sequencing-Based Analysis

Soybean (Glycine max L.) is a major legume crop that is mainly distributed in temperate regions. The adaptability of soybean to grow at relatively high latitudes is attributed to natural variations in major genes and quantitative trait loci (QTLs) that control flowering time and maturity. Identification of new QTLs and map-based cloning of candidate genes are the fundamental approaches in elucidating the mechanism underlying soybean flowering and adaptation. To identify novel QTLs/genes, we developed two F8:10 recombinant inbred lines (RILs) and evaluated the traits of time to flowering (R1), maturity (R8), and reproductive period (RP) in the field. To rapidly and efficiently identify QTLs that control these traits, next-generation sequencing (NGS)-based QTL analysis was performed. This study demonstrates that only one major QTL on chromosome 4 simultaneously controls R1, R8, and RP traits in the Dongnong 50 × Williams 82 (DW) RIL population. Furthermore, three QTLs were mapped to chromosomes 6, 11, and 16 in the Suinong 14 × Enrei (SE) RIL population. Two major pleiotropic QTLs on chromosomes 4 and 6 were shown to affect flowering time, maturity, and RP. A QTL influencing RP was identified on chromosome 11, and QTL on chromosome 16 was associated with time to flowering responses. All these QTLs contributed to soybean maturation. The QTLs identified in this study may be utilized in fine mapping and map-based cloning of candidate genes to elucidate the mechanisms underlying flowering and soybean adaptation to different latitudes and to breed novel soybean cultivars with optimal yield-related traits.